A focus group qualitative study of HIV stigma in the Canadian healthcare system
Bibliographic record
Abstract
Stigma related to HIV in the healthcare system has a pervasive, negative impact on the mental, physical and sexual health of people living with HIV. While well-documented before the advent of antiretroviral treatment, this stigma in Canada has not been as thoroughly examined from a critical perspective since HIV’s evolution from an acute to a chronic illness. The current study examines attitudes and beliefs of healthcare providers toward people living with HIV through the use of focus groups. Focus group participants were women living with HIV, men living with HIV, medical and nursing students, and health care providers working with people living with HIV. Data analysis was conducted with a critical lens using an immersion/ crystallization approach. Two broad themes emerged from the data: HIV-specific experiences, and components of stigma. Both negative and positive experiences were described. Discrimination, as a behavioural act, was deemed to be the less prevalent and often more covert expression of stigmatization. Stereotyping, including with regard to perceived sexuality, and prejudice were seen as more insidious and perpetuated by both the medical and educational establishments. These findings clearly demonstrate the need for change in terms of reducing the amount of stigma present in these complex, nuanced, and enduring relationships between people living with HIV and the health care system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.039 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".